Joaquín M. Piccini

Papers

1

Total Citations

10

H-Index

1

About

Joaquín M. Piccini is a researcher whose work bridges the critical gap between sensor technology and manufacturing quality control, with a primary focus on welding process monitoring and automation. His key research areas include sensor fusion, thermal imaging, and dimensional analysis for real-time industrial applications. Piccini’s major contribution lies in developing a calibration tool that integrates dimensional and thermal sensors to estimate weld penetration depth—a parameter essential for ensuring structural integrity in manufacturing. This work, published in 2021 and garnering 10 citations, demonstrates his ability to combine theoretical modeling with practical sensor integration, offering a non-invasive solution for quality assessment. By fusing data from multiple sensor types, his approach enhances accuracy and reliability in welding diagnostics, addressing a long-standing challenge in automated production. Piccini’s research is particularly notable for its potential to reduce waste and improve safety in industries such as automotive and aerospace. His work reflects a commitment to advancing smart manufacturing through data-driven methods, making him a valuable contributor to the field of industrial automation and process monitoring.

Research Focus

Key Achievements

1
H-Index
1
Papers
10
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
A calibration tool for weld penetration depth estimation based on dimensional and thermal sensor fusion
10 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 4

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 68 days ago